The present invention relates, generally, to a system and method for assessing and predicting failure rates of end items and, in particular, to reliability assessment and prediction of new end items and their respective components and parts based on in-service reliability data for predecessor/similar end items.
Reliability assessment and prediction of failure rates of electrical and mechanical parts is a valuable tool used by a wide array of industries, such as, manufacturers and distributors of automobiles, high-end electrical equipment, household and industrial mechanical equipment, military contract goods, space and space industry equipment, and aircraft and avionics systems. Reliability predictions are often used to assist management in deciding appropriate maintenance schedules, replacement parts needs for immediate use, end-item estimated lifetime, end-item projected costs, and safety analyses.
In the aircraft and avionics industry, the methodology historically used to prepare reliability predictions and support safety analyses has been based on MIL-HDBK-217 (xe2x80x9cMilitary Handbook 217xe2x80x9d). MIL-HDBK-217 was created over two decades ago by the U.S. Department of Defense (xe2x80x9cDODxe2x80x9d) to be used primarily for predicting reliability for comparative purposes. Over the years, observed data relating to various parts, components, and equipment was compiled from a wide range of sources to form the handbook. The handbook contains numerous tables and charts which can be used for predicting the average mean time between failure (xe2x80x9cMTBFxe2x80x9d) of various electrical parts and components. MIL-HDBK-217 was known industry-wide as the standard methodology available for reliability assessment. However, the recent explosion of technology has made the task of updating the number and types of new components and parts nearly impossible. Many industries began looking elsewhere, outside of MIL-HDBK-217, for prediction analyses because the data was either not available for the part of interest or it was grossly outdated. Recognizing that industries were no longer relying on the handbook and that updating was an insurmountable project, the DOD decided to stop updating the handbook in the mid 1990s.
Even though the information contained in MIL-HDBK-217 is outdated, the handbook is still widely used (because a better alternative has yet to be introduced). To accommodate for the deficiencies in updating the handbook, e.g., many of the parts, such as integrated circuits and/or chips, are not listed in the handbook, extensive extrapolation and cross-referencing to older parts is required. This technique poses many problems. For example, it is extremely difficult to determine the applicability and commonality of the older parts listed in the handbook to the new complex integrated circuits. Thus, in many cases, the uncertainty factor of the extrapolated data makes the reliability of the analyses too low.
Unfortunately, even when modified with valid field data, MIL-HDBK-217 consistently yielded a very conservative prediction that did not accurately reflect actual in-service equipment performance. Again, these conservative predictions are due largely to the fact that MIL-HDBK-217 was intended to be used as a uniform method for predicting reliability for comparative purposes, and was not initially intended for predicting xe2x80x9cin-usexe2x80x9d reliability. Overly conservative predictions result in a cost burden to the end user by, for example, unnecessarily indicating a high spare stock requirement, and purchasing unnecessary parts warranty provisions.
A second methodology historically used in the aircraft and avionics industry entails a parts count reliability prediction process which is based on internally developed component failure rates. The failure rates are calculated from millions of device operating hours on commercial aircraft. This process, however, is limited to electrical and electromechanical part types and does not directly reflect mechanical, process, or design-related failure mechanisms.
Another methodology, distributed by Reliability Analysis Center (RAC), is a software tool called PRISM(copyright) and was initially developed to overcome some of the inherent limitations in MIL-HDBK-217. This approach starts at the bottom (the piece-part level) and adds up all the components to eventually obtain a top level model. A bayesian equation is factored in to account for field data.
In general, the traditional prediction methodologies assume that failures are only caused by component faults, defects, or deficiencies and are insufficient to meet current and future program needs. This xe2x80x9cbottoms-upxe2x80x9d approach to reliability focuses on parts as the single source for unreliability of end products. Historically, this has been a reasonable approach due to the relatively low reliability of components in comparison to the impact of higher level assembly process, test, transportation and storage, and human error of application. However, the part defect contribution to the total failure rate has been exacerbated in the harsh environment of avionics and, in some cases, military applications.
Another methodology recently developed by the University of Maryland, called the xe2x80x9cphysics of failurexe2x80x9d approach, focuses on failure models based on the actual physics of the failure, e.g., a solder joint life model based on materials, physical dimensions, and usage environment. This approach is in its infancy in terms of the number of failure models which have been developed as compared to the number needed to perform a successful reliability prediction. In addition, the randomness of all processes, both in the equipment design/build process as well as the processes of all part/material suppliers poses potential problems to this approach. Nonetheless, physics of failure predictions can be useful tools in understanding failure mechanisms and minimizing their risks of occurrence; however, it is not foreseeable that this approach will mature enough to accurately predict in-field reliability of equipment.
Accordingly, an improved reliability prediction system and method is needed to meet a dynamic parts requirement. In addition, a methodology is needed that evaluates data collected from in-field performance.
The present invention overcomes the prior art problems and provides an in-service reliability assessment and prediction system for end items. The system includes a field data source, a new component data source, and a processing means for assessing the similarities and differences between a new equipment design and predecessor equipment.
The methodology of the present invention provides an assessment of reliability of the new equipment by comparing a fielded end item design to a new design, determining the degree of similarity between the two designs, and determining an appropriate method of assessment based on the degree of similarity.
In one embodiment, a similarity analysis process is performed which includes identifying characteristic differences between the fielded end item and the new design, quantifying the impact of each identified difference, compiling the data, and determining the field failure rate of the new design.
In another embodiment, an alternate approach to the similarity analysis is performed which includes determining the level of assessment to be performed, determining the product group for which expected failure rates are used, identifying factors impacting the field failure rate, identifying characteristic differences between the fielded end item and the new design, quantifying the impact of the characteristic differences, compiling the data, and determining the field failure rate of the new design.